Confidence intervals for a spatially generalized, continuous simulation flood frequency model for Great Britain

There is growing interest in the application of "continuous simulation'' conceptual rainfall-runoff models for flood frequency estimation as an adjunct to event-based or statistical design methodology. The approach has advantages that stem from the use of models with continuous water balance accounting. Conceptual rainfall-runoff models usually require calibration, which in turn requires gauged rainfall and flow data. One of the key challenges is therefore to develop ways of generalizing models for use at ungauged sites. Recent work has produced a prototype scheme for achieving this aim in Great Britain for two catchment models by relating model parameters to spatial catchment properties, such as soils, topography, and geology. In this paper we present an analysis of the uncertainty associated with one of the generalized models ( the "probability distributed model'') in terms of confidence intervals for simulations at test sites that are treated as if they were ungauged. This is done by fitting regression relationships between hydrological model parameters and catchment properties so as to estimate the parameters as distribution functions for the ungauged site case. Flood flow outputs are then simulated from the parameter distributions and used to construct approximate confidence intervals. Comparison with gauged data suggests that the generalized model may be tentatively accepted. Uncertainty in the modeled flood flows is often of a similar order to the uncertainty surrounding a more conventional statistical model, in this case a single-site generalized Pareto distribution fitted to the gauged data

Predictors of inhospital mortality following out-of-hospital cardiac arrest: insights from a single-centre consecutive case series

PURPOSE OF THE STUDY: Out-of-hospital cardiac arrest (OHCA) has a poor prognosis despite bystander resuscitation and rapid transfer to hospital. Optimal management of patients after arrival to hospital continues to be contentious, especially the timing of emergency coronary angiography±revascularisation. Robust predictors of inhospital outcome would be of clinical value for initial decision-making.STUDY DESIGN: A retrospective analysis of consecutive patients who presented to a university hospital following OHCA over a 70-month period (2008-2013). Patients were identified from the emergency department electronic patient registration and coding system. For those patients who underwent emergency percutaneous coronary intervention, details were crosschecked with national databases.RESULTS: We identified 350 consecutive patients who were brought to our hospital following OHCA. Return of spontaneous circulation (ROSC) for &gt;20 min was achieved either before arrival or inhospital in 196 individuals. From the 350 subjects, 114 (32.6%) survived to hospital discharge. When sustained ROSC was achieved, either before or inhospital, survival to discharge was 58.2% (114 of 196). Non-shockable rhythm, absence of bystander cardiopulmonary resuscitation, 'downtime' &gt;15 min and initial pH ≤7.11 were predictors of inhospital death. 12% patients who underwent angiography in the presence of ST elevation had no acute coronary occlusion. 21% patients with acute coronary occlusion at angiography did not have ST elevation.CONCLUSIONS: In our cohort of patients with OHCA, those who achieve ROSC had a survival-to-discharge rate of 58.2%. We identified four predictors of inhospital death, which are readily available at the time of patient presentation. Reliance on ST elevation to decide about coronary angiography and revascularisation may be flawed. More data are required.</p